1. Technical Field
This disclosure relates to an automated production system, and in particular to an electronic production system and method for monitoring and controlling production in a facility.
2. Description of the Related Art
Operation of production facilities such as chemical and automotive plants requires production management and accounting on a large scale to attain substantial and consistent quality, to provide economies of scale to improve productivity, and to avoid waste in resources, time, and money.
In facilities employing a multitude of quality and quantity measurements, such as chemical plants in which the amount and type of chemicals produced constitute the inventory of the plant, the coordination, merging, and tracking of processes producing inventory are difficult to attain. Such difficulties may be caused by incompatible production data gathering systems, using, for example, electronic sensors in conjunction with manual readings. Electronic sensors provide improved data gathering, but require supervision and routine calibration.
The tried and true techniques for obtaining manual readings may provide some accuracy, but the procedures for obtaining such readings may be sporadic as well as uneconomical compared to electronic sensors. Data management of such diverse sources of data has been unwieldy in the past.
Other difficulties in inventory management may be caused by incompatible data networking within a facility by the use of different computers and different data formats. Accordingly, the horizontal integration of diverse applications for access of data by an automatic production system has been difficult to achieve.
Some automatic production systems employ a central management system to receive all production data. The incompatible data networking in such a system has prevented effective vertical integration of production data from production processes to the management system of the facility.
Such automatic production systems also use supervisory management systems which are complex to implement and to learn. Some supervisory management systems also find difficulty in handling dynamic process production data.